Course Overview
In this workshop, participants will embark on an overview journey of Deep Learning, Azure AI, and the Evolution of Natural Language Processing (NLP). Designed to provide both conceptual understanding and practical application.
Who should attend
- Developers and software engineers interested in learning GenerativeAI
- AI enthusiasts and professionals aiming to build intelligent and innovative solutions
- Even Data scientists and machine learning practitioners seeking to enhance their skills in working with OpenAI models
Prerequisites
- No prior knowledge of Generative AI is required
- Familiarity with the fundamentals of Data and Azure cloud
- Knowledge of Jupyter Lab or Google Colaboratory notebooks
- Hands-on experience with Python programming language will be a plus
Outline: Foundation for Generative AI (FGAI)
DeepLearning
- DeepLearning Basics & Artificial Neural Network Overview
- Building the Vocabulary – Terms & Concepts
- Training the Neural Networks
- Key Types of Neural Networks – CNN, RNN, LSTM, GANs
- Lab(s): Working with Neural Networks
Deep Learning on Azure
- Azure AI Framework
- Various ways to develop AI Applications on Azure
- Examples of each of the options
- Getting started with Azure AI
- Lab(s): Getting started with Azure OpenAI Studio
Evolution of Natural Language Processing
- Introduction to NLP
- Rule-Based Approaches: Keyword matching and grammar rules
- Statistical Methods: n-grams
- Machine Learning for tasks like part-of-speech tagging, named entity recognition
- Word embeddings: Word2Vec, GloVe for semantic relationships
- Attention Mechanisms: Machine translation, text summarization, sentiment analysis
- Transformers: Architecture, self-attention, pre-trained language models like BERT, GPT
- Skip Connections and Layer Norm
- Feed-forward Layer
- Transformer hyperparameters and Why they work so well
- BERT, T5 , GPT
- Lab(s): NLP use cases with key approaches